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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Kritprajun, Paychuda Tolbert, Leon M. Sun, Jingjing Wang, Jingxin Praisuwanna, Nattapat Liu, Yunting Ferrari, Maximiliano The University of Tennessee Department of Electrical Engineering and Computer Science KnoxvilleTN United States The Pennsylvania State University Department of Electrical Engineering University ParkPA United States Oak Ridge National Laboratory Grid Components and Control Oak RidgeTN United States

ISBN: (纸本)9798350316445

This paper presents a state of charge (SOC) management strategy to ensure low-voltage ride-through (LVRT) services of a grid-connected photovoltaic (PV) with a supercapacitor (SC) energy storage system (PVSS). A concept of SOC reservation for LVRT operations is introduced to guarantee that the PV grid-connected system can provide LVRT services complying with grid code requirements. SOC management is derived by considering SC limitations, the current rating of the converters, and grid conditions. Therefore, safe operation of the power system and PVSS can be achieved. The study also adopts an electrothermal model of the SC to adjust the current set points during SOC management by considering the temperature-dependent SC parameters;thus, both safety and full utilization of the SC can be achieved. Consequently, SOC management can rapidly be accomplished, thereby increasing the certainty of providing LVRT services to the system. © 2023 IEEE.

关键词： Grid-connected photovoltaic system low-voltage ride-through state of charge management supercapacitor

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Sequential load restoration with decision-dependent 5G base station backup batteries for resilient distribution systems

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Applied Energy 2025年 396卷

作者： Song, Meng Bai, Wenchao Lu, Shuai Wen, Jianfeng Sun, Wei Hu, Qinran Ban, Mingfei School of Electrical Engineering Southeast University Nanjing China Department of Electrical Engineering University of Liverpool Liverpool United Kingdom Electrical Engineering University of Central Florida Florida United States College of Computer and Control Engineering Northeast Forestry University Harbin China

-Spare backup batteries of numerous 5G base stations (BSs) can provide considerable flexibility for DS restoration. Meanwhile, their operations are tightly coupled with distribution system (DS) restoration decisions. However, the decision-dependent behaviors of 5G BSs were mostly ignored in previous studies, potentially hindering the DS's secure operation and rapid restoration. To bridge this gap, we have formulated a three-stage model for the operational evolution of 5G BSs. Firstly, backup batteries power BS communication during the outage. In the following two stages, as the DS power is restored, BSs are re-energized, and the backup batteries' spare capacity is leveraged to assist DS load restoration through demand response (DR). Furthermore, a bi-level optimization model is proposed to coordinate sequential load restoration and 5G BS operation, aiming for safer and faster load restoration, with the three evolution stages of 5G BSs seamlessly integrated. This model is solved intractably as nonlinearity terms and non-convex lower-level formulation. Thus, the model linearization is conducted, and a reformulated Column-and-Constraint Generation (R-CCG) method is utilized to handle the fault of Karush-Kuhn-Tucker (KKT) conditions. Numerical results demonstrate that the proposed methodology can accurately capture the decision-dependent characteristic of 5G BS and effectively enhance the DS resilience process. © 2025 Elsevier Ltd

关键词： Restoration

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Biological Influence of Low-Frequency Electromagnetic Field Exposition Based on Selected Cell Death Markers 15

Biological Influence of Low-Frequency Electromagnetic Field ...

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15th International Conference Elektro, ELEKTRO 2024

作者： Cichorowski, Robert Kocikowska, Olga Bajtos, Marek Radil, Roman Janousek, Ladislav De Carrillo, Daria Gendosz Student, Sebastian Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Gliwice Poland Faculty of Automatic Control Electronics and Computer Science Department of Engineering and Systems Biology Gliwice Poland Silesian University of Medicine Faculty of Medical Sciences Department of Physiology Katowice Poland Faculty of Electrical Engineering and Informational Technology Department of Electromagnetic and Biomedical Engineering Žilina Slovakia Silesian University of Medicine Faculty of Medical Sciences in Zabrze Department of Histology Zabrze Poland Silesian University of Technology Biotechnology Center Gliwice Poland

ISBN: (纸本)9798350372359

This work presents the results of the examination of the HeLa cell line exposure on the ELF-EMF (extremely low-frequency electromagnetic field). In particular, the relationship between ELF-EMF exposition time and cell death. The examination of cell death hallmarks were examined by estimation levels of selected proteins - FACL4 (a protein that is a part of the ferroptosis pathway) and CK18 (Cytokeratin related to necrosis and apoptosis pathways) in the proposed model of workers exposed to ELF-EMF week. © 2024 IEEE.

关键词： Electromagnetic fields

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Data-Driven Model for Human Tracking and Prediction Using Kalman Filter with Particle Swarm Optimization 3rd

Data-Driven Model for Human Tracking and Prediction Using Ka...

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3rd International Conference on control, Instrumentation and Mechatronics engineering, CIM 2022

作者： Ajasa, Abiodun Afis Nawawi, Sophan Wahyudi Department of Control and Mechatronics Engineering School of Electrical Engineering Universiti Teknologi Malaysia Johor Malaysia Department of Electronics and Computer Engineering Faculty of Engineering Lagos State University Epe Campus Lagos Nigeria

ISBN: (纸本)9789811939228

Intelligent monitoring systems have evolved due to technological improvement and innovation in biometric identification technology and protecting lives and property. As a result, intelligent monitoring systems are becoming increasingly prevalent. Consequently, this paper proposes the development of an IoT-based Human Tracking system that incorporates the Kalman Filter (KF) Algorithm. Apart from the deployment of the Kalman Filter, analysis was also done with an optimized Kalman filter with PSO (KF-PSO) using Particle Swarm Optimization. Rather than manually tuning the process noise error, R, and measurement error, Q, which are involved in KF, PSO was also used to adjust the errors to obtain their best values for optimal estimation. As a result, a two-dimensional (2D) Kalman filter is developed. The positions and velocities of the object being tracked (i.e., humans) are estimated in x- and y-directions. The proposed system has been evaluated using ten different human datasets, each consisting of 100 samples. The quality performance of KF and KF-PSO models was also compared using accuracy analysis. In comparison, the KF-PSO model yielded an average Mean-Square error of 17 mm (i.e., 1.7% error), while the conventional KF model gave an average Mean-Square error of 22 mm (i.e., 2.2% error). Hence, the KF-PSO model is a better filter than the conventional KF model because of its higher accuracy. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Kalman filters

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User Input Search - Custom Motion Estimation Algorithm Optimized for UAVs

User Input Search - Custom Motion Estimation Algorithm Optim...

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Proceedings of the International Convention MIPRO

作者： J. Benjak D. Hofman Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing Zagreb Croatia

Unmanned aerial vehicle technology is growing rapidly as it finds its application in the various industries, including military & defense, agriculture, logistics, transportation, healthcare, entertainment and many others. One of the fastest growing industries including drones is the entertainment industry. More specifically, First Person View (FPV) piloting has become a popular sport which attracts huge masses. In FPV systems, the pilot wears FPV goggles and controls the drone using a controller, and the drone transmits video data to the goggles in real time. Since drones usually fly very quickly, the video quality in terms of resolution, compression artefacts and end-to-end delay must be maintained. This paper explores the idea of optimizing the Motion Estimation (ME) algorithm of existing High Efficiency Video Coding (HEVC) algorithms by utilizing user input from the controller. For example, if the drone is directed to hover to the left, then it would make sense to search for the most similar blocks in the previous video frame only on the left side of the referent block. For the purpose of this research, a HEVC video coder was customized to receive additional input besides the video data – the user input from the controller, or in other words, drone movement directions. We call this ME algorithm User Input Search (UIS). Our UIS algorithm is compared with the standard ME algorithms and its efficiency is tested.

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Mask R-CNN Based Real Time near Drowning Person Detection System in Swimming Pools

Mask R-CNN Based Real Time near Drowning Person Detection Sy...

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2022 Mohammad Ali Jinnah University International Conference on Computing, MAJICC 2022

作者： Hayat, Muhammad Aftab Yang, Goutian Iqbal, Atif School of Control & Computer Engineering North China Electric Power University Beijing China The University of Lahore Department of Electrical Engineering Lahore Pakistan

ISBN: (数字)9781665475198

ISBN: (纸本)9781665475198

To find the drowning person in time in swimming pool to reduce the drowning person mortality rate. We used the Mask R-CNN algorithm, and optimizing the convolution backbone of the traditional Mask R-CNN algorithm by adding features of cascaded with pyramid model to design a swimmer drowning detection system. Through real-time recognition of the posture of swimmers in the swimming pool, it can determine the drowning person and alert in time. The system's proposed algorithm has been put to the test on multiple real-world video sequences taken in swimming pools, and the findings show that it is very accurate and capable of monitoring people in real time. The experimental results show that the detection speed of the system is 6 FPS, while the detection rate is 94.1 %, while the false detection rate is 5.9%. The effect is good, which satisfying the anticipated requirements. © 2022 IEEE.

关键词： Swimming pools

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Cross-Modality Image Transformation Using Generative Adversarial Network 24th

Cross-Modality Image Transformation Using Generative Adversa...

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24th Conference on Man-Machine-Environment System engineering, MMESE 2024

作者： Liu, Haoting Yu, Shiqi Hou, Qingwen Chen, Shuai Guo, Kuiyuan Wang, Xu Li, Qing Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Research Institute of Trustworthy Autonomous Systems Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China CATARC Technology Co. Ltd. Shenzhen518118 China

ISBN: (纸本)9789819771387

A cross-modality image transformation method using the Generative Adversarial Network (GAN) is proposed in this paper. First, the preprocessing methods are performed to the original image data. The computational steps include adjusting image size and suppressing image noises. Second, a kind of GAN is constructed. Both the generator network and discriminator network are created. Third, the GAN is trained and the back propagation optimization is performed continuously. Finally, the trained GAN can be used for data enhancement. To test the effects of computational steps above, the image transformation from the visible light image to other noise-contaminated image is performed. Lots of experiments have illustrated the correctness of our method. © Beijing KeCui Man-Machine-Environment System engineering Technology Research Academy 2024.

关键词： Generative adversarial networks

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Development of a Converter-based Supercapacitor System Emulator for PV Applications

Development of a Converter-based Supercapacitor System Emula...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Kritprajun, Paychuda Sutton, Elizabeth Tolbert, Leon M. Liu, Yunting Wang, Jingxin Praisuwanna, Nattapat Ferrari, Maximiliano The University of Tennessee Department of Electrical Engineering and Computer Science KnoxvilleTN United States The Pennsylvania State University Department of Electrical Engineering University ParkPA United States Grid Components and Control Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (纸本)9798350316445

As the utilization of supercapacitors in power system applications continues to increase, it is important to observe their behavior under transient and long-term operations in order to understand their impact on power grids. A real-time reconfigurable hardware testbed (HTB) is a power network emulator that provides flexibility to study various power system scenarios. This paper presents an emulation of a supercapacitor for a photovoltaic (PV) system on the HTB platform such that its dynamic behavior during power system scenarios can be observed. The developed emulator on the HTB is verified by comparing the emulation results with the model developed in MATLAB/Simulink. The experimental results of the emulator are consistent with the simulation results under the grid support scenarios. This supercapacitor emulator can be potentially used for various power system scenarios in addition to the PV applications presented in this paper. © 2023 IEEE.

关键词： grid ancillary services grid-connected photovoltaic system hardware testbed supercapacitor

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Integration of ANN for Accurate Estimation and control in Wastewater Treatment 28

Integration of ANN for Accurate Estimation and Control in Wa...

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28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Ţiru, Andreea Elena Vasiliev, Iulian Diaconu, Larisa Vilanova, Ramon Voipan, Daniel Ratnaweera, Harsha Dunǎrea de Jos University of Galaţi Department of Automatic Control and Electrical Engineering Galaţi Romania Autonomous University of Barcelona Department of Automation Systems and Advanced Control Research Barcelona Spain Dunǎrea de Jos University of Galaţi Department of Computer Science and Information Technology Galaţi Romania Ås Norway

ISBN: (纸本)9798350339918

The management of wastewater is a significant global concern that calls for innovative solutions to lessen its negative effects on the environment. Conventional techniques of treating wastewater need improvement in order to deal with newly discovered contaminants, which highlights the importance of providing precise estimates of process performance and resource requirements. The worsening water shortage situation requires a paradigm shift in which wastewater is viewed as a useful resource. It is possible to create an economy that is both sustainable and circular by treating and recycling wastewater, putting less pressure on freshwater supplies, and leaving as little of an environmental footprint as possible. This study investigates the use of Artificial Neural Networks (ANNs) as software estimators in the treatment of wastewater, with a particular emphasis on predicting ammonium concentrations in effluent. In order to deal with imbalanced time-series data, the research introduces innovative data pretreatment strategies. These techniques include a Sliding Window protocol, Data Normalization, and a K-Fold training scheme. This illustrates the potential of ANNs to revolutionize wastewater treatment procedures and drive developments in this field. The suggested method demonstrates higher performance when estimating pollutant concentrations, showing the ability of ANNs to do so. © 2023 IEEE.

关键词： Neural networks

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Contrast enhancement of optical videoscope images

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Iran Journal of computer Science 2023年第3期6卷 261-275页

作者： Ammar, Reda Aboshosha, Sahar El-Hag, Noha A. Saifeldeen, Reda El-Shafai, Walid El-Banby, Ghada M. Ashiba, Huda I. Khalaf, Ashraf A. M. Elazm, Atef Abou El-Rabaie, El-Sayed M. Abd El-Samie, Fathi E. El-Safrawey, Amir Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Department of Electronics and Electrical Comm. Faculty of Engineering Minia University Minya Egypt Department of Management of Information Systems Higher Institute of Commercial Science El-Mahala El-Kobra Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Department of Electronics and Electrical Communications Engineering Bilbis Higher Institute of Engineering Sharqia Bilbis Egypt Security Engineering Laboratory Computer Science Department Prince Sultan University Riyadh 11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia

The videoscope (VS) images have poor quality and low contrast. Hence, in this paper, three proposed frameworks to improve the quality of VS images are presented. The first framework depends on contrast-limited adaptive histogram equalization (CLAHE) with adaptive gamma correction. The second framework depends on homomorphic processing. The third framework is based on the homomorphic enhancement with histogram equalization. The first one is superior from the entropy perspective, while the third one is superior from the contrast perspective. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023.

关键词： Fuzzy enhancement Histogram equalization Homomorphic enhancement Spectral entropy

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